A number of commercial assay techniques are based on the biorecognition of a target species by a suitable receptor species. One area of particular interest arises where the target species is a biomarker, namely a substance whose presence in a biological sample might be measured and evaluated as an indicator of normal biological processes, pathogenesis, or a pharmacological response to therapeutic intervention. For example, assay techniques capable of detecting protein biomarkers can be of substantial clinical value, given their intimate association with current biological function.
Accordingly, the quantified detection of biomarkers in biological media, such as blood sera, holds enormous promise both for the early detection of disease or physiological misfunction and for the subsequent tracking of disease progression in response to therapy. A consensus is emerging that early detection and personalized treatment in clinics, based on genetic and proteomic profiles of perhaps four to twenty key biomarkers, could give rise to substantial improvements in the survival rates of patients suffering from a range of complex infectious, autoimmune, cancer and cardiac diseases.
A wide variety of strategies, such as those based on enzyme-linked immunosorbent assay (ELISA), surface plasmon resonance (SPR) and electroanalysis, have already been developed with the aim of achieving selective detection of different biomarkers.
In many such assay systems, some form of labelling (e.g., radioactive, enzymatic or fluorescent labelling) is an essential prerequisite for achieving the necessary selectivity and sensitivity in the biorecognition event and its subsequent reporting. Unfortunately, labelling can be associated with numerous problems, such as cost issues, impractical assay timescales, potential perturbations caused by the label and the generation of non-specific signals.
On the other hand, label-free methods are also associated with significant practical challenges, including the need for much greater sensitivity to the underlying biorecognition event (a consequence of the absence of a label that is specifically designed to respond strongly when the biorecognition event takes place), while nonetheless retaining high specificity to the target species.
A number of label-free methods based on electrochemical techniques have, nonetheless, been developed. In very general terms, an electrical biosensor reports on the capturing of a biological species by an electrode-confined corresponding receptor species through a current or voltage signal (or a perturbation thereof) generated at the electrode.
In principle, a number of different electrochemical techniques might be utilised, in each case resulting in the interrogation of different aspects of the electrochemical properties of the electrode and its local environment. For example, voltammetric methods have been proposed whereby the current response to an applied voltage is measured on a system in which a receptor such as an antibody is confined to the electrode surface. Such methods have an advantage in terms of their conceptual simplicity, but they do not necessarily provide satisfactory selectivity or sensitivity for biomarkers present at inherent very low levels in biological samples.
A different approach makes use of electrochemical impedance spectroscopy (EIS), which is a technique that monitors changes in capacitance or charge-transfer resistance associated with the specific binding of certain materials to a suitably modified electrode surface.
Two distinct classes of EIS methods can be distinguished. In “non-faradaic EIS”, no external redox active probe is typically added to the system and so the signal response reflects purely non-faradaic impedance characteristics. On the other hand, in “faradaic EIS” a discrete, typically solution-phase, redox probe is added in large excess to the system. Generally, this is done with the aim of increasing signal magnitude, on the basis that the resistive effects of the biorecognition event at the electrode surface should be amplified by sampling the impact of the biorecognition on the current generated by the redox probe.
Although EIS-based techniques have the potential to give rise to highly sensitive and specific assays, they can suffer from problems associated, for example, with the modelling assumptions inherent in signal analysis (conventional analysis relies on fitting the experimental data using a simple Randles-like circuit model). In addition, still further improvements in sensitivity and selectivity would be desirable. Ideally this would also be achievable without the need to add a redox probe to the analytical solution.
As a result, there remains a need for the provision of further assay methods suitable for the detection of target species such as biomarkers. Of particular value would be methods that are robust and not reliant on modelling assumptions, which are highly selective to the target species of interest and which have sensitivities that compare favourably, and preferably surpass, those achievable with current state-of-the-art methods.